IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v17y2024i13p3147-d1422339.html
   My bibliography  Save this article

Cost-Effectiveness of Predictive Maintenance for Offshore Wind Farms: A Case Study

Author

Listed:
  • Rasmus Dovnborg Frederiksen

    (Department of Materials and Production, Aalborg University, 9220 Aalborg, Denmark)

  • Grzegorz Bocewicz

    (Faculty of Electronics and Computer Science, Koszalin University of Technology, 75-453 Koszalin, Poland)

  • Grzegorz Radzki

    (Faculty of Electronics and Computer Science, Koszalin University of Technology, 75-453 Koszalin, Poland)

  • Zbigniew Banaszak

    (Faculty of Electronics and Computer Science, Koszalin University of Technology, 75-453 Koszalin, Poland)

  • Peter Nielsen

    (Department of Materials and Production, Aalborg University, 9220 Aalborg, Denmark)

Abstract

The successful implementation of predictive maintenance for offshore wind farms suffers from a poor understanding of the consequential short-term impacts and a lack of research on how to evaluate the cost-efficiency of such efforts. This paper aims to develop a methodology to explore the short-term marginal impacts of predictive maintenance applied to an already existing preventive maintenance strategy. This method will be based on an analysis of the performance of the underlying predictive model and the costs considered under specific maintenance services. To support this analysis, we develop a maintenance efficiency measure able to estimate the efficiency of both the underlying prediction model used for predictive maintenance and the resulting maintenance efficiency. This distinction between the efficiency of the model and the service results will help point out insufficiencies in the predictive maintenance strategy, as well as facilitate calculations on the cost–benefits of the predictive maintenance implementation. This methodology is validated on a realistic case study of an annual service mission for an offshore wind farm and finds that the efficiency metrics described in this paper successfully support cost–benefit estimates.

Suggested Citation

  • Rasmus Dovnborg Frederiksen & Grzegorz Bocewicz & Grzegorz Radzki & Zbigniew Banaszak & Peter Nielsen, 2024. "Cost-Effectiveness of Predictive Maintenance for Offshore Wind Farms: A Case Study," Energies, MDPI, vol. 17(13), pages 1-24, June.
  • Handle: RePEc:gam:jeners:v:17:y:2024:i:13:p:3147-:d:1422339
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/17/13/3147/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/1996-1073/17/13/3147/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Kusiak, Andrew & Li, Wenyan, 2011. "The prediction and diagnosis of wind turbine faults," Renewable Energy, Elsevier, vol. 36(1), pages 16-23.
    2. Sun, Lingyun & Yin, Jiemin & Bilal, Ahmad Raza, 2023. "Green financing and wind power energy generation: Empirical insights from China," Renewable Energy, Elsevier, vol. 206(C), pages 820-827.
    3. Yeter, B. & Garbatov, Y. & Guedes Soares, C., 2020. "Risk-based maintenance planning of offshore wind turbine farms," Reliability Engineering and System Safety, Elsevier, vol. 202(C).
    4. Irawan, Chandra Ade & Ouelhadj, Djamila & Jones, Dylan & Stålhane, Magnus & Sperstad, Iver Bakken, 2017. "Optimisation of maintenance routing and scheduling for offshore wind farms," European Journal of Operational Research, Elsevier, vol. 256(1), pages 76-89.
    5. Xiaobo Liu & Yen-Lin Chen & Lip Yee Por & Chin Soon Ku, 2023. "A Systematic Literature Review of Vehicle Routing Problems with Time Windows," Sustainability, MDPI, vol. 15(15), pages 1-20, August.
    6. Gatzert, Nadine & Kosub, Thomas, 2016. "Risks and risk management of renewable energy projects: The case of onshore and offshore wind parks," Renewable and Sustainable Energy Reviews, Elsevier, vol. 60(C), pages 982-998.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Fallahi, F. & Bakir, I. & Yildirim, M. & Ye, Z., 2022. "A chance-constrained optimization framework for wind farms to manage fleet-level availability in condition based maintenance and operations," Renewable and Sustainable Energy Reviews, Elsevier, vol. 168(C).
    2. uit het Broek, Michiel A.J. & Veldman, Jasper & Fazi, Stefano & Greijdanus, Roy, 2019. "Evaluating resource sharing for offshore wind farm maintenance: The case of jack-up vessels," Renewable and Sustainable Energy Reviews, Elsevier, vol. 109(C), pages 619-632.
    3. Chandra Ade Irawan & Dylan Jones, 2019. "Formulation and solution of a two-stage capacitated facility location problem with multilevel capacities," Annals of Operations Research, Springer, vol. 272(1), pages 41-67, January.
    4. Sadeghian, Omid & Mohammadpour Shotorbani, Amin & Mohammadi-Ivatloo, Behnam & Sadiq, Rehan & Hewage, Kasun, 2021. "Risk-averse maintenance scheduling of generation units in combined heat and power systems with demand response," Reliability Engineering and System Safety, Elsevier, vol. 216(C).
    5. Galina Chebotareva & Inna Čábelková & Wadim Strielkowski & Luboš Smutka & Anna Zielińska-Chmielewska & Stanislaw Bielski, 2023. "The Role of State in Managing the Wind Energy Projects: Risk Assessment and Justification of the Economic Efficiency," Energies, MDPI, vol. 16(12), pages 1-26, June.
    6. Wang, Yadong & Wang, Delu & Shi, Xunpeng, 2023. "Sustainable development pathways of China's wind power industry under uncertainties: Perspective from economic benefits and technical potential," Energy Policy, Elsevier, vol. 182(C).
    7. Cai, Yanpeng & Cai, Jianying & Xu, Linyu & Tan, Qian & Xu, Qiao, 2019. "Integrated risk analysis of water-energy nexus systems based on systems dynamics, orthogonal design and copula analysis," Renewable and Sustainable Energy Reviews, Elsevier, vol. 99(C), pages 125-137.
    8. Ma, Yuanchi & Liu, Yongqian & Bai, Xinjian & Guo, Yuanjun & Yang, Zhile & Wang, Liyuan & Tao, Tao & Zhang, Lidong, 2024. "DivideMerge: A multi-vessel optimization approach for cooperative operation and maintenance scheduling in offshore wind farm," Renewable Energy, Elsevier, vol. 229(C).
    9. Boudy Bilal & Kaan Yetilmezsoy & Mohammed Ouassaid, 2024. "Benchmarking of Various Flexible Soft-Computing Strategies for the Accurate Estimation of Wind Turbine Output Power," Energies, MDPI, vol. 17(3), pages 1-36, February.
    10. Marcin Rabe & Dalia Streimikiene & Yuriy Bilan, 2019. "The Concept of Risk and Possibilities of Application of Mathematical Methods in Supporting Decision Making for Sustainable Energy Development," Sustainability, MDPI, vol. 11(4), pages 1-24, February.
    11. Stock-Williams, Clym & Swamy, Siddharth Krishna, 2019. "Automated daily maintenance planning for offshore wind farms," Renewable Energy, Elsevier, vol. 133(C), pages 1393-1403.
    12. Nguyen, Ho Si Hung & Do, Phuc & Vu, Hai-Canh & Iung, Benoit, 2019. "Dynamic maintenance grouping and routing for geographically dispersed production systems," Reliability Engineering and System Safety, Elsevier, vol. 185(C), pages 392-404.
    13. Mehrjoo, Mehrdad & Jafari Jozani, Mohammad & Pawlak, Miroslaw, 2021. "Toward hybrid approaches for wind turbine power curve modeling with balanced loss functions and local weighting schemes," Energy, Elsevier, vol. 218(C).
    14. Rubio-Domingo, G. & Linares, P., 2021. "The future investment costs of offshore wind: An estimation based on auction results," Renewable and Sustainable Energy Reviews, Elsevier, vol. 148(C).
    15. Albert H. Schrotenboer & Evrim Ursavas & Iris F. A. Vis, 2019. "A Branch-and-Price-and-Cut Algorithm for Resource-Constrained Pickup and Delivery Problems," Transportation Science, INFORMS, vol. 53(4), pages 1001-1022, July.
    16. Jin, Xin & Ju, Wenbin & Zhang, Zhaolong & Guo, Lianxin & Yang, Xiangang, 2016. "System safety analysis of large wind turbines," Renewable and Sustainable Energy Reviews, Elsevier, vol. 56(C), pages 1293-1307.
    17. Chiacchio, Ferdinando & D’Urso, Diego & Famoso, Fabio & Brusca, Sebastian & Aizpurua, Jose Ignacio & Catterson, Victoria M., 2018. "On the use of dynamic reliability for an accurate modelling of renewable power plants," Energy, Elsevier, vol. 151(C), pages 605-621.
    18. Igliński, Bartłomiej & Iglińska, Anna & Koziński, Grzegorz & Skrzatek, Mateusz & Buczkowski, Roman, 2016. "Wind energy in Poland – History, current state, surveys, Renewable Energy Sources Act, SWOT analysis," Renewable and Sustainable Energy Reviews, Elsevier, vol. 64(C), pages 19-33.
    19. Liu, Xiaoran & Ronn, Ehud I., 2020. "Using the binomial model for the valuation of real options in computing optimal subsidies for Chinese renewable energy investments," Energy Economics, Elsevier, vol. 87(C).
    20. Rafael Dawid & David McMillan & Matthew Revie, 2018. "Decision Support Tool for Offshore Wind Farm Vessel Routing under Uncertainty," Energies, MDPI, vol. 11(9), pages 1-17, August.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jeners:v:17:y:2024:i:13:p:3147-:d:1422339. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.